Quantile regression offers a more complete statistical model than mean regression and now
has widespread applications. Consequently, we provide a review of this technique. We …

A complete resource for finance students, this textbook presents the most common empirical
approaches in finance in a comprehensive and well-illustrated manner that shows how …

Quantile regression is gradually emerging as a unified statistical methodology for estimating
models of conditional quantile functions. By complementing the exclusive focus of classical …

Quantile regression, as introduced by Koenker and Bassett (1978), may be viewed as an
extension of classical least squares estimation of conditional mean models to the estimation …

In reinforcement learning (RL), an agent interacts with the environment by taking actions and
observing the next state and reward. When sampled probabilistically, these state transitions …

Quantile regression (QR) has received increasing attention in recent years and applied to
wide areas such as investment, finance, economics, medicine and engineering. Compared …

Fully revised and restructured, Measuring Market Risk, Second Edition includes a new
chapter on options risk management, as well as substantial new information on parametric …

Given the growing need for managing financial risk, risk prediction plays an increasing role
in banking and finance. In this study we compare the out-of-sample performance of existing …

Market Risk Analysis is the most comprehensive, rigorous and detailed resource available
on market risk analysis. Written as a series of four interlinked volumes each title is self …

This paper presents a new approach to estimating the conditional probability distribution of
multiperiod financial returns. Estimation of the tails of the distribution is particularly important …